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<p>Nitrification and denitrification are two important biological processes producing N<sub>2</sub>O in soils, but their contributions to N<sub>2</sub>O emissions are not well understood, hindering precise mitigation measures. Here, we developed process-based models (PBM) with and without transport (T) to partition N<sub>2</sub>O sources by tracking nitrogen flows (NF) through different reaction pathways. The model with transport (PBM-T-NF) well predicted N<sub>2</sub>O production from nitrification and denitrification in two different repacked soils with a shallow depth of 8&#xa0;mm under moisture conditions ranging from 40 to 100% water-filled pore space (WFPS), demonstrating its robustness and reliability. In comparison, the model without transport (PBM-NF) failed to capture the N<sub>2</sub>O dynamics and the relative contribution of denitrification to N<sub>2</sub>O production (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10533_2025_1246_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">\({C}_{D}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>C</mi> <mi>D</mi> </msub> </math></EquationSource> </InlineEquation>), highlighting the need of including mass transport in predicting N<sub>2</sub>O dynamics. The PBM-T-NF model was further employed to investigate the effects of soil properties on N<sub>2</sub>O emissions and sources. Increased NH<sub>4</sub><sup>+</sup> concentration significantly decreased <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10533_2025_1246_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">\({C}_{D}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>C</mi> <mi>D</mi> </msub> </math></EquationSource> </InlineEquation> under relatively low moisture conditions, while increased NO<sub>3</sub><sup>−</sup> slightly promoted <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10533_2025_1246_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">\({C}_{D}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>C</mi> <mi>D</mi> </msub> </math></EquationSource> </InlineEquation> over different moisture contents, emphasizing the importance of substrate availability and moisture conditions in controlling <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10533_2025_1246_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">\({C}_{D}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>C</mi> <mi>D</mi> </msub> </math></EquationSource> </InlineEquation><i>.</i> Furthermore, the PBM-T-NF model was used to quantify N<sub>2</sub>O sources from an artificial soil core of 80&#xa0;mm depth. Soil depth was shown to be important in mediating <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10533_2025_1246_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">\({C}_{D}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>C</mi> <mi>D</mi> </msub> </math></EquationSource> </InlineEquation> by controlling O<sub>2</sub> diffusivity, which is highly dependent on moisture content. Given the long-standing challenge in experimental quantification of N<sub>2</sub>O sources from soils, our developed model provides a novel way to estimate N<sub>2</sub>O production from different nitrogen processes, which is key for accurately targeting mitigation of N<sub>2</sub>O emissions from soils.</p>

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Identifying soil N2O sources by combining laboratory experiments with process-based models

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月9日

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  • Zhifeng Yan,
  • Zhaopei Chu,
  • Balázs Grosz,
  • Baoxuan Chang,
  • Narasinha Shurpali,
  • Gang Liu,
  • Zhaolei Li,
  • Jinsen Zheng,
  • Si-liang Li,
  • Klaus Butterbach-Bahl

摘要

Nitrification and denitrification are two important biological processes producing N2O in soils, but their contributions to N2O emissions are not well understood, hindering precise mitigation measures. Here, we developed process-based models (PBM) with and without transport (T) to partition N2O sources by tracking nitrogen flows (NF) through different reaction pathways. The model with transport (PBM-T-NF) well predicted N2O production from nitrification and denitrification in two different repacked soils with a shallow depth of 8 mm under moisture conditions ranging from 40 to 100% water-filled pore space (WFPS), demonstrating its robustness and reliability. In comparison, the model without transport (PBM-NF) failed to capture the N2O dynamics and the relative contribution of denitrification to N2O production ( \({C}_{D}\) C D ), highlighting the need of including mass transport in predicting N2O dynamics. The PBM-T-NF model was further employed to investigate the effects of soil properties on N2O emissions and sources. Increased NH4+ concentration significantly decreased \({C}_{D}\) C D under relatively low moisture conditions, while increased NO3− slightly promoted \({C}_{D}\) C D over different moisture contents, emphasizing the importance of substrate availability and moisture conditions in controlling \({C}_{D}\) C D . Furthermore, the PBM-T-NF model was used to quantify N2O sources from an artificial soil core of 80 mm depth. Soil depth was shown to be important in mediating \({C}_{D}\) C D by controlling O2 diffusivity, which is highly dependent on moisture content. Given the long-standing challenge in experimental quantification of N2O sources from soils, our developed model provides a novel way to estimate N2O production from different nitrogen processes, which is key for accurately targeting mitigation of N2O emissions from soils.